Identification of single spectral lines through supervised machine learning in a large HST survey (WISP): a pilot study for Euclid and WFIRST

@article{Baronchelli2020IdentificationOS,
  title={Identification of single spectral lines through supervised machine learning in a large HST survey (WISP): a pilot study for Euclid and WFIRST},
  author={I. Baronchelli and C. M. Scarlata and G. Rodighiero and L. Rodr{\'i}guez-Mu{\~n}oz and M. Bonato and M. Bagley and A. Henry and M. Rafelski and M. Malkan and J. Colbert and Y. Dai and H. Dickinson and C. Mancini and V. Mehta and L. Morselli and H. I. Teplitz},
  journal={arXiv: Astrophysics of Galaxies},
  year={2020}
}
  • I. Baronchelli, C. M. Scarlata, +13 authors H. I. Teplitz
  • Published 2020
  • Physics
  • arXiv: Astrophysics of Galaxies
  • Future surveys focusing on understanding the nature of dark energy (e.g., Euclid and WFIRST) will cover large fractions of the extragalactic sky in near-IR slitless spectroscopy. These surveys will detect a large number of galaxies that will have only one emission line in the covered spectral range. In order to maximize the scientific return of these missions, it is imperative that single emission lines are correctly identified. Using a supervised machine-learning approach, we classified a… CONTINUE READING

    References

    SHOWING 1-10 OF 27 REFERENCES
    The WFC3 infrared spectroscopic parallel (WISP) survey
    • 90
    • Highly Influential
    • PDF
    The DEIMOS 10k spectroscopic survey catalog of the COSMOS field
    • 50
    • PDF
    Euclid: ESA's mission to map the geometry of the dark universe
    • 65
    CANDELS: The Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey
    • 1,115
    • PDF